The aim of this sub-proposal is twofold: to develop HPC implementations of proven segmentation, registration and visualization techniques; to develop new image acquisition, segmentation, registration and visualization capabilities using HPC as an enabling technology. High Performance Computing will be used in the NAC to drive rapid and/or interactive analysis of large image based data-sets. Specifically: 1. We will apply the utility of parallel algorithms and make use of dedicated supercomputing hardware (MPP, SMP and cluster machines) to design and develop a number of applications which are now in routine clinical use. 2. We will utilize recent hardware and software technology developments which have made HPC much less expensive and easier to apply to medical image analysis problem. We will exploit these technology improvements by developing symmetric multi-processor and cluster optimized applications for image acquisition, segmentation, registration and visualization. These implementations will achieve high performance, be highly portable and easy to disseminate.